Previous |  Up |  Next

Article

Keywords:
interval-valued problem; multiobjective programming; exact l$_1$ penalty function; LU-efficient solution
Summary:
Our objective in this article is to explore the idea of an unconstrained problem using the exact l$_1$ penalty function for the nonsmooth multiobjective interval-valued problem (MIVP) having inequality and equality constraints. First of all, we figure out the KKT-type optimality conditions for the problem (MIVP). Next, we establish the equivalence between the set of weak LU-efficient solutions to the problem (MIVP) and the penalized problem (MIVP$_\rho$) with the exact l$_1$ penalty function. The utility of this transformation lies in the fact that it converts constrained problems to unconstrained ones. To accurately predict the applicability of the results presented in the paper, meticulously crafted examples are provided.
References:
[1] Antczak, T.: $(p,r)$-invex sets and functions. J. Math. Anal. Appl. 263 (2001), 355-379. DOI 10.1006/jmaa.2001.7574 | MR 1866053
[2] Antczak, T.: Exact penalty functions method for mathematical programming problems involving invex functions. Europ. J. Oper. Res. 198 (2009), 29-36. DOI  | MR 2508030
[3] Antczak, T.: The exact l$_1$ penalty function method for constrained nonsmooth invex optimization problems. In: System Modeling and Optimization Vol. 391 of the series IFIP Advances in Information and Communication Technology (2013) (D. Hömberg and F. Tröltzsch, eds.), pp. 461-470. DOI  | MR 3409747
[4] Antczak, T.: Exactness property of the exact absolute value penalty function method for solving convex nondifferentiable interval-valued optimization problems. J. Optim. Theory Appl. 176 (2018), 205-224. DOI  | MR 3749691
[5] Antczak, T.: Optimality conditions and duality results for nonsmooth vector optimization problems with the multiple interval-valued objective function. Acta Math. Scientia 37 (2017), 1133-1150. DOI  | MR 3657212
[6] Antczak, T., Farajzadeh, A.: On nondifferentiable semi-infinite multiobjective programming with interval-valued functions. J. Industr. Management Optim. 19(8) (2023), 1-26. DOI  | MR 4562617
[7] Antczak, T., Studniarski, M.: The exactness property of the vector exact $l_1$ penalty function method in nondifferentiable invex multiobjective programming. Functional Anal. Optim.37 (2016), 1465-1487. DOI  | MR 3579015
[8] Bazaraa, M. S., Sherali, H. D., Shetty, C. M.: Nonlinear Programming: Theory and Algorithms. John Wiley and Sons, New York 1991. MR 0533477 | Zbl 1140.90040
[9] Ben-Israel, A., Mond, B.: What is invexity. J. Austral. Math. Soc. Series B 28 (1986). 1-9. DOI 10.1017/S0334270000005142 | MR 0846778
[10] Bertsekas, D. P., Koksal, A. E.: Enhanced optimality conditions and exact penalty functions. In: Proc. Allerton Conference, 2000.
[11] Craven, B. D.: Invex functions and constrained local minima. Bull. Austral. Math. Soc. 24 (1981), 357-366. DOI 10.1017/S0004972700004895 | MR 0647362
[12] Clarke, F. H.: Optimization and Nonsmooth Analysis. Wiley, New York 1983. MR 0709590
[13] Fletcher, R.: An exact penalty function for nonlinear programming with inequalities. Math. Programm. 5 (1973), 129-150. DOI  | MR 0329644
[14] Ha, N. X., Luu, D. V.: Invexity of supremum and infimum functions. Bull. Austral. Math. Soc. 65 (2002), 289-306. DOI  | MR 1898543
[15] Hanson, M. A.: On sufficiency of the Kuhn-Tucker conditions. J. Math. Anal. Appl. 80 (1981), 545-550. DOI 10.1016/0022-247X(81)90123-2 | MR 0614849
[16] Jayswal, A., Stancu-Minasian, I., Ahmad, I.: On sufficiency and duality for a class of interval-valued programming problems. Appl. Math. Comput. 218 (2011), 4119-4127. DOI  | MR 2862082
[17] Jayswal, A., Banerjee, J.: An exact l$_1$ penalty approach for interval-valued programming problem. J. Oper. Res. Soc. China 4 (2016), 461-481. DOI  | MR 3572965
[18] Mangasarian, O. L.: Sufficiency of exact penalty minimization. SIAM J. Control Optim. 23 (1985), 30-37. DOI  | MR 0774027
[19] Martin, D. H.: The essence of invexity. J. Optim. Theory Appl. 42 (1985), 65-76. DOI 10.1007/BF00941316 | MR 0802390
[20] Moore, R. E.: Interval Analysis. Prentice-Hall, Englewood Cliffs 1966. MR 0231516
[21] Moore, R. E.: Methods and applications of interval analysis. Soc. Industr. Appl. Math., Philadelphia 1979. MR 0551212
[22] Pietrzykowski, T.: An exact potential method for constrained maxima. SIAM J. Numer. Anal. 6 (1969), 299-304. DOI  | MR 0245183
[23] Reiland, T. W.: Nonsmooth invexity. Bull. Austral. Math. Soc. 42 (1990), 437-446. DOI  | MR 1083280
[24] Khatri, S., Prasad, A. K.: Duality for a fractional variational formulation using $\eta $-approximated method. Kybernetika 59(5) (2023), 700-722. DOI  | MR 4681018
[25] Weir, T., Jeyakumar, V.: A class of nonconvex functions and mathematical programming. Bull. Austral. Math. Soc. 38 (1988), 177-189. DOI 10.1017/S0004972700027441 | MR 0969907
[26] Wu, H. C.: The Karush-Kuhn-Tucker optimality conditions in an optimization problem with interval-valued objective function. Europ, J. Oper. Res. 176 (2007), 46-59. DOI  | MR 2265133
[27] Wu, H. C.: Wolfe duality for interval-valued optimization. J. Optim. Theory Appl. 138 (2008), 497-509. DOI  | MR 2429694
[28] Zangwill, W. I.: Non-linear programming via penalty functions. Management Sci. 13 (1967), 344-358. DOI  | MR 0252040
[29] Zhang, J.: Optimality condition and Wolfe duality for invex interval-valued nonlinear programming problems. J. Appl. Math. Article ID 641345 (2013). DOI  | MR 3142560
[30] Zhou, H. C., Wang, Y. J.: Optimality condition and mixed duality for interval-valued optimization. Fuzzy Inform. Engrg.2 (2009), 1315-1323. DOI  | MR 2429694
Partner of
EuDML logo